Data encoding reduces data required to represent various information such as text, graphics, video and audio. In common data coding or compression schemes, an encoder uses information to compress or encode data and a decoder employs the same information to decompress or decode the data. FIG. 1 illustrates a common coding method and system such as Moving Picture Experts Group (MPEG)/H.264 in which the side information is available to both the encoder 102 and the decoder 104. For instance, the encoder 102 compresses data X using the side information Y and the decoder 104 uses the same side information Y to decode the data it receives into X′. Other coding methods use decoder only side information to decompress data. Wyner-Ziv coding scheme is one such example. FIG. 2 illustrates a coding method and system with decoder only side information such as the Wyner-Ziv coding. The encoder 202 codes data X and is sent to a receiver. The receiving end generates side information Y at 206 and the decoder 204 decodes the data X into X′ using the side information Y.
Data-compression with decoder-only side information is of interest in several applications including, but not limited to, low complexity encoding of media, data communication over error-prone channels, distributed source coding for sensor networks, etc. In a practical system of source coding with decoder-only side information, the encoder does no have knowledge of the side information which the decoder will use in decoding. On one hand the encoder may use a rate that is too low and cause decoding failure. Rate refers to the amount of encoded data (e.g., the amount of bits) used per unit of time (e.g., seconds) to represent continuous medium such as video and audio. On the other hand, if the encoder uses a rate that is too high, the system will not achieve the best attainable compression performance.
Currently, data-compression systems with decoder only side information employ non-iterative side information generation process and decoding process in decompression. These methods are described in B. Girod, A. Aaron, S. Rane, and D. Rebollo-Monedero, “Distributed video coding,” Proceedings of the IEEE, vol. 93, pp. 71-83, January 2005; A. Majumdar, J. Chou, and K. Ramchandran, “Robust distributed video compression based on multilevel coset codes,” in Conference record of ASILOMAR, 2003, pp. 845-849; H. Wang and A. Ortega, “WZS: Wyner-Ziv scalable predictive video coding,” in Picture Coding Symposium, 2004; Q. Xu and Z. Xiong, “Layered Wyner-Ziv video coding,” in Proc. Video Coding and Image Processing, 2004; A. Sehgal, A. Jagmohan, and N. Ahuja, “Wyner-ziv coding of video: an error-resilient compression framework,” IEEE Transactions on Multimedia, vol. 6, pp. 249-258, April 2004; and A. Sehgal, A. Jagmohan, and N. Ahuja, “Scalable video coding using Wyner-Ziv codes,” in Picture Coding Symposium, 2004. In these systems, the decoder generates the side information and then uses it to decode the received signal. This solution is not robust since if the encoder has not transmitted enough bits to recover the source from the decoder side information incorrect decoding occurs. In addition, the incorrect decoding compounds into poor decoder reconstruction quality and error propagation in future reconstructions. Known techniques address this problem by providing a feedback channel used to inform the encoder if there is decoding failure so that the encoder can transmit more information (or bits) to the decoder until the data is decoded successfully. However, this solution is not feasible in practice, since the requirement of a feedback channel is usually unrealistic and expensive.